Professorship (W3) - Machine Learning in Agriculture

vor 2 Wochen

NordrheinWestfalen, Deutschland Rheinische Friedrich-Wilhelms-Universität Bonn - Landwirtschaftliche Fakultät Vollzeit

to be filled at the earliest possible date.
Machine learning is an increasingly important method in science. To exploit the full potential of this general method for agriculture, we are looking for a person who can demonstrate relevant, internationally visible scientific work on developing methods or applications of machine learning.
The successful candidate is expected to contribute to the Cluster of Excellence EXC 2070 PhenoRob and help develop future interdisciplinary and transdisciplinary research initiatives of the faculty. Thus, the application of machine learning in the field of agriculture, especially in the context of crop production, is essential for future work but not a prerequisite for this position. A possible field of research could be the fusion of process-based and data-driven models.
Success in acquiring and implementing third-party-funded projects is a pre-requisite. In teaching, the subject area is to be represented in both mandatory and elective courses in the B.Sc. and M.Sc. degree programs of the Faculty of Agricultural, Nutritional, and Engineering Sciences.

The formal requirements are regulated by §36 Hochschulgesetz NRW.

The University of Bonn is committed to diversity and equal opportunity. It is certified as a family-friendly university and has a Dual-Career Service. It aims to increase the proportion of women in areas where women are
underrepresented and to particularly facilitate their careers.
Therefore, the University of Bonn strongly encourages applications from qualified women. Applications are be handled in accordance with the Landesgleichstellungsgesetz NRW.
Applications from qualified individuals with a certified severe disability and from those of equal status are particularly welcome.

For further information on this professorship, please contact the chair of the appointments committee, Prof. Dr. Haunert, by email ( ). Applications submitted by 30/11/2024 are guaranteed to be considered.

Please apply via our application web portal:
.

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